Abstract
Assembly sequence planners require information such as eligible assembly sequences and constraints to generate feasible assembly plans. This information can be, for example, encoded in the form of a precedence matrix. This paper presents a knowledge-driven approach that integrates ontological reasoning with geometry and topology-aware properties to systematically generate precedence matrices. We use a bottom-up assembly approach to generate ontological reasoning rules by identifying an initial part and then successively attaching directly connected components until the entire assembly is complete. We implement an ontology-based reasoning framework in which Semantic Web Language rules encode and enforce priority relationships among parts based on their direct connectivity and assembly constraints. Each rule captures a specific precedence condition. We validate the correctness and generality of these rules by applying them to multiple, structurally diverse products. The reasoning mechanism reliably infers sound precedence constraints for each evaluated assembly, producing a correct partial order of operations from which valid assembly or disassembly sequences can be generated.